code: def to_deeper_graph(graph):
      """deeper graph"""
  
      weighted_layer_ids = graph.deep_layer_ids()
      if len(weighted_layer_ids) >= Constant.MAX_LAYERS:
          return None
  
      deeper_layer_ids = sample(weighted_layer_ids, 1)
  
      for layer_id in deeper_layer_ids:
          layer = graph.layer_list[layer_id]
          new_layer = create_new_layer(layer, graph.n_dim)
          graph.to_deeper_model(layer_id, new_layer)
      return graph
  
file_path: nni/nni/algorithms/hpo/networkmorphism_tuner/graph_transformer.py
imports: from copy import deepcopy
  from random import randrange, sample
  from .graph import NetworkDescriptor
  from .layers import StubDense, StubReLU, get_batch_norm_class, get_conv_class, get_dropout_class, get_pooling_class, is_layer
  from .utils import Constant
label_desc: Use image node_id 4 for calling a global function with example usage: to_deeper_graph(graph) and returns: graph, None